Information processing apparatus, information processing method, and program

ABSTRACT

There is provided an information processing apparatus including a stable section detection unit configured to detect a stable section of a posture of a sensor device that a user wears, based on first sensor data provided from the sensor device, a specific action section detection unit configured to detect a specific action section in which a specific action of the user occurs, based on second sensor data, and asleep section detection unit configured to detect a sleep section in which the user is in a sleep state, based on a relationship between the stable section and the specific action section.

TECHNICAL FIELD

The present disclosure relates to an information processing apparatus,an information processing method, and a program.

BACKGROUND ART

Many technologies for analyzing a sleep state, which is a fundamentalbehavior of a human, have already been proposed. For example, PatentLiterature 1 describes a technology for presenting a user with anevaluation of quality of sleep, based on a measurement result of abiological signal during sleep.

CITATION LIST Patent Literature

Patent Literature 1: JP 2013-52165A

SUMMARY OF INVENTION Technical Problem

In recent years, the miniaturization of a sensor device makes itpossible for a user to acquire a log of activities while wearing thesensor device routinely as well as during sleep. Incidentally, thetechnology described in Patent Literature 1 is based on the assumptionthat the user is in a sleep state. That is, these technologies analyzewhat the user's sleep state is like, but do not determine whether or notthe user is in the sleep state. Hence, it cannot be said that thesetechnologies are sufficient to detect or analyze a user's sleep statealong with a user's daily activities.

Therefore, in the present disclosure, there are provided novel andimproved information processing apparatuses, information processingmethods, and programs that can detect and analyze a user's sleep statealong with a user's daily activities.

Solution to Problem

According to the present disclosure, there is provided an informationprocessing apparatus including a stable section detection unitconfigured to detect a stable section of a posture of a sensor devicethat a user wears, based on first sensor data provided from the sensordevice, a specific action section detection unit configured to detect aspecific action section in which a specific action of the user occurs,based on second sensor data, and a sleep section detection unitconfigured to detect a sleep section in which the user is in a sleepstate, based on a relationship between the stable section and thespecific action section.

Additionally, according to the present disclosure, there is provided aninformation processing method including detecting a stable section of aposture of a sensor device that a user wears, based on first sensor dataprovided from the sensor device, detecting a specific action section inwhich a specific action of the user occurs, based on second sensor data,and detecting, by a processor, a sleep section in which the user is in asleep state, based on a relationship between the stable section and thespecific action section.

In addition, according to the present disclosure, there is provided aprogram for causing a computer to execute a function of detecting astable section of a posture of a sensor device that a user wears, basedon first sensor data provided from the sensor device, a function ofdetecting a specific action section in which a specific action of theuser occurs, based on second sensor data, and a function of detecting asleep section in which the user is in a sleep state, based on arelationship between the stable section and the specific action section.

Advantageous Effects of Invention

According to the present disclosure described above, it is possible todetect or analyze a user's sleep state along with a user's dailyactivities.

Note that the effects described above are not necessarily limited, andalong with or instead of the effects, any effect that is desired to beintroduced in the present specification or other effects that can beexpected from the present specification may be exhibited.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing a schematic configuration of a systemaccording to a first embodiment of the present disclosure.

FIG. 2 is a diagram for describing a principle of sleep sectiondetection in the first embodiment of the present disclosure.

FIG. 3 is a block diagram showing a schematic functional configurationof an information processing apparatus, which can perform sleep sectiondetection, according to a first embodiment of the present disclosure.

FIG. 4 is a diagram for describing a processing flow of sleep sectiondetection in the first embodiment of the present disclosure.

FIG. 5 is a block diagram showing a schematic configuration of a systemaccording to a second embodiment of the present disclosure.

FIG. 6 is a diagram for describing a selective use of detectors in afourth embodiment of the present disclosure.

FIG. 7 is a block diagram showing a hardware configuration of aninformation processing apparatus according to an embodiment of thepresent disclosure.

DESCRIPTION OF EMBODIMENTS

Hereinafter, preferred embodiments of the present disclosure will bedescribed in detail with reference to the appended drawings. Note that,in this specification and the drawings, elements that have substantiallythe same function and structure are denoted with the same referencesigns, and repeated explanation is omitted.

Note that description will be provided in the following order.

1. First Embodiment 1-1. Configuration of System 1-2. Principle of SleepSection Detection 1-3. Functional Configuration of InformationProcessing Apparatus 1-4. Processing Flow of Sleep Section Detection 2.Second Embodiment 3. Third Embodiment 4. Fourth Embodiment 5. ExampleApplication of Detection Result 6. Hardware Configuration 7.Supplemental Remarks 1. First Embodiment 1-1. Configuration of System

FIG. 1 is a block diagram showing a schematic configuration of a systemaccording to a first embodiment of the present disclosure. Referring toFIG. 1, a system 10 includes a sensor device 100 and a smartphone 200.The sensor device 100 includes a sensor 110, a pre-processing unit 120,and a memory 130. The smartphone 200 includes a position detection unit210, a sensor 220, a behavior recognition unit 230, a processing unit240, an integrated analysis unit 250, a storage 260, and an application270.

(Sensor Device) The sensor device 100 is a wearable device. The sensordevice 100 is directly attached to a user, for example, by being woundaround a user's wrist, angle, or finger. Alternatively, the sensordevice 100 may be indirectly attached to the user by being fixed to agarment by using a clip or the like. Note that although the sensordevice 100 is a device that is attached to the user, the sensor device100 need not be always necessarily attached to the user. For example,the sensor device 100 may be detached while the user is taking a bath oris getting ready. Therefore, as described below, a case where adetection value of an acceleration sensor included in the sensor 110 isnot changed may include a case where the user wears the sensor device100 and is in a stable posture and a case where the sensor device 100 isdetached and left somewhere.

As described above, the sensor device 100 includes, in addition to thesensor 110, a processor (realizing the pre-processing unit 120) thatprocesses sensor data acquired by the sensor 110, a storage device(realizing the memory 130) that stores the sensor data or the processeddata, and a communication device (not shown) that transmits the sensordata or the processed data to the smartphone 200. The sensor device 100including the processor may be an information processing apparatusaccording to an embodiment of the present disclosure. The informationprocessing apparatus can be realized using a hardware configuration tobe described below. In the following, the respective elements of thesensor device 100 will be described.

The sensor 110 includes various types of sensors provided in the sensordevice 100 and senses a behavior of the user wearing the sensor device100. For example, the sensor 110 includes an acceleration sensor. Aposture or a body movement of the user wearing the sensor device 100 canbe specified based on an acceleration sensor detection value acquired bythe acceleration sensor. In addition, the sensor 110 may include othersensors, such as an angular velocity sensor, a gyro sensor, an opticalsensor, a sound sensor, or an atmospheric pressure sensor. Detectionvalues of these sensors also can be used for specifying the posture orthe body movement of the user. Furthermore, the sensor 110 may include acamera for acquiring an image of the user, or a microphone for acquiringa voice uttered by the user. The sensor data acquired by the sensor 110may be temporarily stored in the memory 130 after processing by thepreprocessing unit 120, or may be directly stored in the memory 130without undergoing the pre-processing.

The pre-processing unit 120 performs the pre-processing on the sensordata acquired by the sensor 110. For example, the pre-processing unit120 extracts a feature amount from the sensor data. Also, thepre-processing unit 120 may remove noise contained in the sensor dataand resample the sensor data. Note that, in the present embodiment, itis desirable that the processing of the sensor data by thepre-processing unit 120 can restore raw data of the sensor data or dataclose to the raw data from the processed data. In addition, in someexamples of the present embodiment, all or part of analysis processingperformed in the processing unit 240 of the smartphone 200 may beperformed by the pre-processing unit 120.

The memory 130 stores the sensor data that has undergone the processingby the pre-processing unit 120, or the raw data of the sensor data thathas not undergone the pre-processing. The data stored in the memory 130is transmitted to the smartphone 200 by the communication device (notshown). The communication between the sensor device 100 and thesmartphone 200 can use, for example, radio communication such asBluetooth (registered trademark).

(Smartphone)

The smartphone 200 is a terminal device that the user carries separatelyfrom the sensor device 100. The smartphone 200 is realized by, forexample, a hardware configuration of an information processing apparatusto be described below. Also, the smartphone 200 may be replaced withother terminal device that can implement a similar function, such as atablet terminal, for example. In the following, the respective elementsof the smartphone 200 will be described.

The position detection unit 210 is realized by, for example, a globalpositioning system (GPS) receiver. In this case, the position detectionunit 210 acquires position information of the smartphone 200 byreceiving a radio wave from a satellite. Alternatively, the positiondetection unit 210 may be realized by a communication device thatperforms radio communication such as WiFi. In this case, the positiondetection unit 210 acquires the position information of the smartphone200 based on position information of a radio-communication base stationor a received state of radio wave from the base station.

Similar to the sensor 110 of the sensor device 100, the sensor 220 mayinclude various sensors, such as an acceleration sensor, an angularvelocity sensor, a gyro sensor, an optical sensor, a sound sensor, anatmospheric pressure sensor, a camera, and a microphone. In the presentembodiment, unlike the sensor device 100, the smartphone 200 may beplaced on a desk while the user is working, the smartphone 200 may beput in a bag while the user is moving, or the smartphone 200 may beplaced near a bed while the user is asleep. Therefore, the sensor 110 ofthe sensor device 100 is mainly used to acquire information indicatingthe posture or the body movement of the user. On the other hand, unlikethe sensor device 100 requiring a reduction in size and weight in orderfor attachment to the user, some degree of volume or weight is allowableto the smartphone 200. Hence, the sensor 220 can include more types ofsensors than the sensor 110 or can include sensors having higheraccuracy than the sensor 110.

The behavior recognition unit 230 is realized by, for example, aprocessor. The behavior recognition unit 230 recognizes user behaviorbased on the position information of the smartphone 200 detected by theposition detection unit 210 and/or the sensor data provided from thesensor 220. For the recognition of the behavior using the positioninformation and the sensor data, various known technologies can be used,and thus, a detailed description thereof will be omitted herein. Asdescribed below, in the present embodiment, the user behavior recognizedby the behavior recognition unit 230 is used in combination with dataanalysis result from the sensor device 100. In another example, the userbehavior recognized by the behavior recognition unit 230 may be used bythe application 270 or the like, separately from the data analysisresult from the sensor device 100.

The processing unit 240 is realized by, for example, a processor. Theprocessing unit 240 performs analysis processing on the data receivedfrom the sensor device 100 by the communication device (not shown). Forexample, the processing unit 240 detects a sleep section, in which theuser wearing the sensor device 100 has been in a sleep state, byanalyzing the sensor data of the sensor 110. Incidentally, details ofthe processing of sleep section detection will be described below. Asdescribed above, all or part of the analysis processing performed by theprocessing unit 240 may be realized in a distributed manner by thepre-processing unit 120 of the sensor device 100.

The integrated analysis unit 250 is realized by, for example, aprocessor. The integrated analysis unit 250 integrates the user behaviorrecognition result by the behavior recognition unit 230 and the sleepsection detection result by the processing unit 240. In this way, byintegrating the user behavior recognition result based on differentdata, for example, the user behavior that is missing in the respectiveresults can be complemented, the accuracy of the result can be improvedby adjusting the results to match with each other, and false detectioncan be prevented. The user behavior recognition result integrated by theintegrated analysis unit 250 is stored in the storage 260. Aside fromthis, the user behavior analysis result by the behavior recognition unit230 or the sleep section detection result by the processing unit 240also may be stored in the storage 260.

The storage 260 is realized by, for example, a memory or a storagedevice. The user behavior recognition result acquired by the processingof the sensor device 100 and the smartphone 200 is accumulated in thestorage 260. For example, a user behavior log, a position informationlog, number of steps, a sleep time log, and the like are accumulated inthe storage 260. Such data is generated based on, for example, thebehavior recognition result by the behavior recognition unit 230 and thesleep section detection result by the processing unit 240. The logs,which are temporarily or persistently accumulated in the storage 260,are used by the application 270.

The application 270 is application software that is executed by thesmartphone 200 and uses the user behavior log. The application 270 isexecuted by the processor of the smartphone 200 and uses an outputdevice such as a display or a speaker, or an input device such as atouch panel as necessary. In addition, the application 270 may transmita control signal to an external device through the communication deviceor transmit information toward other users. A specific example of theapplication 270 will be described below.

1-2. Principle of Sleep Section Detection

Next, the principle of the sleep section detection according to thefirst embodiment will be described.

FIG. 2 is a diagram for describing the principle of the sleep sectiondetection in the first embodiment of the present disclosure, FIG. 2shows a time change in a detection value of a 3-axis acceleration sensorincluded in the sensor 110 of the sensor device 100. In the following,the time divided into sections P1 to P7 in the shown example will bedescribed.

In the sections P1, P3, P5, and P7, the detection value of theacceleration sensor is continuously and greatly changed. In thissection, it is estimated that the user conducts various activities in awaking state. On the other hand, in the sections P2 and P6, thedetection value of the acceleration sensor is constant without change.Also, in the section P4, the detection value of the acceleration sensoris constant for a while, is then changed in a short time, and isconstant again for a while. In the section P4, such a change isrepeated.

As described below, the case where the detection value of theacceleration sensor is not changed may include the case where the userwears the sensor device 100 and is in the stable posture and the casewhere the sensor device 100 is detached and left somewhere. In order fordetecting the sleep section of the user, it is necessary to distinguishthese cases from each other. Here, the present inventors focused on thefact that, in a case where the user is in the sleep state, the body ofthe user is not stationary for quite a while, but the posture of theuser is occasionally changed and is then stationary again. Such a userbehavior is observed as, for example, turning-over. The turning-over isa very natural behavior found in many users.

In the present embodiment, the sleep state of the user is defined as astate in which first sections in which the posture of the user remainsunchanged (section in which the detection value of the accelerationsensor is constant without change) and second sections in which theposture of the user is converted (section in which the detection valueof the acceleration sensor is changed and which is sufficiently shorterthan the first period) are repeated. On the contrary, in a case wherethe user detaches the sensor device 100, it is considered that after thedetection value of the acceleration sensor is constant without changefor quite a while, the sensor device 100 is attached again to the userand thus the continuous change of the detection value is resumed.Therefore, the case where the user wears the sensor device 100 and is inthe stable posture and the case where the sensor device 100 is detachedand left somewhere can be identified by the presence or absence of thesecond section before and after the first section.

Referring again to FIG. 2, based on such knowledge, in the sections P2and P6, the detection value of the acceleration sensor is constantwithout change, but in the sections (sections P1, P3, P5, and P7) inwhich the detection value is changed before and after the sections P2and P6, all detection values are continuously changed, and also, thelength of these sections is not always shorter than the sections P2 andP6. Therefore, these sections are estimated as not the case where theuser wears the sensor device 100 and is in the stable posture but thecase where the sensor device 100 is detached and left somewhere.

On the other hand, in the section P4, first sections in which thedetection value of the acceleration sensor is constant without changeand second sections in which the detection value of the accelerationsensor is changed between the first sections in a relatively short timeare repeated. Therefore, in the section P4, it is estimated that theuser wears the sensor device 100 and is in the stable posture.

Note that, strictly speaking, the case where the user wears the sensordevice 100 and is in the stable posture is not the same as the casewhere the user in the sleep state. However, in the present embodiment,the case where the user wears the sensor device 100 and is in the stableposture is considered as the case where the user is in the sleep state.For example, even in a case where the user is still watching a TV orreading a book, the posture of the user is stable, but it is consideredthat a stable time is shorter than the case where the user is in a sleepstate, or the posture of the user is slightly changed. In these cases,for example, in the sensor data analysis processing, an average value ora variance value of acceleration for determining that the posture of thesensor device is in a stable state is appropriately set, and the firstsection can be recognized and identified only when the stable state iscontinued over a predetermined length. Alternatively, in a case where apart of the body of the user wearing the sensor device 100 is known,whether the user is in a sleep state or in a stable state other than thesleep state can be identified according to the direction of the sensordevice 100. Also, it may be considered that the user is lying down butis in a non-sleep state. However, in this case, it may be consideredthat the user is in a sleep state.

So far, the principle of the sleep section detection according to thepresent embodiment has been described. In the following, a functionalconfiguration of an information processing apparatus for detecting asleep section of a user based on the above-described principle will befurther described.

1-3. Functional Configuration of Information Processing Apparatus

FIG. 3 is a block diagram showing a schematic functional configurationof an information processing apparatus, which can perform sleep sectiondetection, according to a first embodiment of the present disclosure.Referring to FIG. 3, an information processing apparatus 300 includes asensor data acquisition unit 301, a stable section detection unit 303, aspecific action section detection unit 305, a sleep section detectionunit 307, an external device control unit 309, and a notificationinformation output unit 311. In the present embodiment, the informationprocessing apparatus 300 is realized by a processor included in a sensordevice 100 or a smartphone 200.

For example, the information processing apparatus 300 may be realized inthe smartphone 200. In this case, when corresponding to the elements ofthe smartphone 200 shown in FIG. 1, the sensor data acquisition unit301, the stable section detection unit 303, the specific action sectiondetection unit 305, and the sleep section detection unit 307 correspondto the processing unit 240, and the external device control unit 309 andthe notification information output unit 311 correspond to theapplication 270. Also, the sleep section detection unit 307 maycorrespond to both the processing unit 240 and the integrated analysisunit 250.

In addition, for example, the information processing apparatus 300 maybe realized in a distributed manner by the sensor device 100 and thesmartphone 200. In this case, when corresponding to the elements of thesensor device 100 and the smartphone 200 shown in FIG. 1, the sensordata acquisition unit 301, the stable section detection unit 303, thespecific action section detection unit 305, and the sleep sectiondetection unit 307 correspond to the processing unit 120 of the sensordevice 100, and the external device control unit 309 and thenotification information output unit 311 correspond to the application270 of the smartphone 200.

Note that the elements for realizing the information processingapparatus 300 are not limited to the above-described example, and avariety of other examples are possible within the scope obvious from thedescription of the present specification to those skilled in the art.For example, the entire functions of the information processingapparatus 300 may be realized in the sensor device 100. Also, forexample, in a case where the information processing apparatus 300 isrealized in a distributed manner by the sensor device 100 and thesmartphone 200, the sleep section detection unit 307 is realized by thepre-processing unit 120 of the sensor device 100 and the processing unit240 and/or the integrated analysis unit 250 of the smartphone 200.

In the following, the respective elements of the information processingapparatus 300 will be further described.

The sensor data acquisition unit 301 is realized by a processor as asoftware interface that acquires sensor data provided from the sensordevice 100. The sensor data may be data that is output by varioussensors, such as an acceleration sensor, an angular velocity sensor, agyro sensor, an optical sensor, a sound sensor, an atmospheric pressuresensor, a camera, or a microphone, which is included in the sensor 110,and is processed by the pre-processing unit 120 as necessary. Inaddition, the sensor data, which is acquired by the sensor dataacquisition unit 301, includes first sensor data to be used by thestable section detection unit 303, and second sensor data to be used bythe specific action section detection unit 305. Such data may be thesame data, for example, the detection value of the common accelerationsensor, or may be different data.

The stable section detection unit 303 detects a stable section of theposture of the sensor device 100, based on the first sensor dataacquired by the sensor data acquisition unit 301. The stable section isa section that becomes a candidate for the first section described abovewith reference to FIG. 2. As in the present embodiment, for example, thestable section of the posture of the sensor device 100 is defined as thesection in which the posture of the sensor device 100 has beenunchanged. For example, in a case where the first sensor data includesthe detection value of the acceleration sensor, the stable sectiondetection unit 303 detects the stable section as the section in whichthe detection value is unchanged. The stable section may be limited to asection that is longer than a predetermined time (for example, severalminutes). However, as already described above, since the detected stablesection is only the stable section of the posture of the sensor device100, whether or not the user wears the sensor device 100 and is in astable posture and whether or not the sensor device 100 is detached andleft somewhere are not specified by the stable section detection resultalone. Therefore, in the present embodiment, specific action sectiondetection is performed by the specific action section detection unit 305to be described below.

The specific action section detection unit 305 detects a specific actionsection in which a specific action of a user occurs, based on the secondsensor data acquired by the sensor data acquisition unit 301. Thespecific action section is a section corresponding to the second sectiondescribed above with reference to FIG. 2. In the present embodiment,similar to the first sensor data, the second sensor data includes thedetection value of the acceleration sensor. Also, in the presentembodiment, the specific action section is a section in which theposture of the user is changed. Also, in the stable section, it isnecessary to consider the probability that the sensor device 100 isdetached, but in the sections (including the specific action section)other than the stable section, the probability that the sensor device100 is detached is negligibly low. Therefore, in the present embodiment,in the sections other than the stable section, the change in the postureof the sensor device 100, which is indicated by the second sensor data,can be considered as the change in the posture of the user.

More specifically, for example, the specific action section detectionunit 305 may detect the specific action section on the condition that(1) the specific action occurs subsequently to the stable section havinga certain length (for example, several minutes or more), (2) thedetection value of the acceleration sensor is changed in a sufficientlyshorter time than the stable section, and (3) another stable section inwhich the detection value of the acceleration sensor is stable at adifferent value from the previous stable section occurs subsequently.

The sleep section detection unit 307 detects the sleep section in whichthe user is in a sleep state, based on a relationship between the stablesection detected by the stable section detection unit 303 and thespecific action section detected by the specific action sectiondetection unit 305. In the present embodiment, in a case where thestable section and the specific action section are repeated, the sleepsection detection unit 307 detects a sleep section including the stablesection and the specific action section. In the example described abovewith reference to FIG. 2, the section P4 is the sleep section, but inthe section P4, the first sections (stable sections) in which thedetection value of the acceleration sensor is constant without changeand the second sections (specific action sections) in which thedetection value of the acceleration sensor is changed between the firstsections in a relatively short time are repeated.

More specifically, for example, the sleep section detection unit 307 maydetect, as the sleep section, the sections from (1) the first stablesection occurring subsequently to the non specific action sectionthrough (2) the specific action section subsequent to the first stablesection and (3) a middle stable section interposed between the previousand next specific action sections to (4) the last stable section whichoccurs subsequently to the last specific action section and to which thenon specific action section is subsequent. In this case, a start time ofthe stable section of (1) can be specified as a sleep start time of theuser, and an end time of the stable section of (4) can be specified as asleep end time of the user.

Also, by using the function of the integrated analysis unit 250 of thesmartphone 200, the sleep section detection unit 307 may determines thesleep section in consideration of matching with the user behaviorrecognized based on the position information or the sensor data by thebehavior recognition unit 230. In this case, the sleep section detectionunit may detect the sleep section further based on the user behaviorthat is recognized based on the sensor data different from the first andsecond sensor data.

Both the external device control unit 309 and the notificationinformation output unit 311, which are to be described below, have afunctional configuration to use the sleep section detection result bythe sleep section detection unit 307. In such a functionalconfiguration, either or both of the external device control unit 309and the notification information output unit 311 may be included in theinformation processing apparatus 300. Also, in the present embodiment,since the method of using the sleep section detection result is notparticularly limited, a functional configuration different from both theexternal device control unit 309 and the notification information outputunit 311 may be present for using the sleep section detection result.Also, the sleep section detection result by the sleep section detectionunit 307 may be stored in the storage as it is and may be used by aseparate device from the information processing apparatus 300.

In a case where the sleep section of the user is detected by the sleepsection detection unit 307, the external device control unit 309 outputsa control signal of the external device. For example, in a case wherethe start of the sleep section is detected, the external device controlunit 309 outputs a control signal for stopping or pausing the externaldevice. Also, as is apparent from the above description, the sleepsection detection by the sleep section detection unit 307 is enabled forthe first time through the specific action section detection occurringafterwards. Therefore, in the present embodiment, the external devicecontrol unit 309 cannot transmit the control signal in real time whenthe sleep state of the user is started. Therefore, in the presentembodiment, the control signal transmitted by the external devicecontrol unit 309 may be transmitted so as to stop or pause the externaldevice, for example, a TV or an air conditioner (according totemperature), which is considered as unnecessary when the user enters asleep state.

Alternatively, the external device control unit 309 may output a controlsignal for causing the external device to set an alarm based on a starttime of the sleep section. The external device used herein is merely anexternal device with respect to the device indicated as the informationprocessing apparatus 300 in FIG. 3. Therefore, for example, in a casewhere the information processing apparatus 300 is realized in thesmartphone 200, other functional elements of the smartphone 200(including those realized by the processor as in the informationprocessing apparatus 300) also may correspond to the external device(the same applies to the case where the information processing apparatus300 is realized by the sensor device 100). Therefore, the externaldevice control unit 309 may be realized by, for example, the processorof the smartphone 200, and may transmit the control signal with respectto the alarm function realized by the processor of the same smartphone200. By automatically setting the alarm based on the start time of thesleep time, for example, it is possible to prevent the user fromoversleeping.

The notification information output unit 311 outputs information fornotifying other user of the sleep section detection result by the sleepsection detection unit 307. For example, the notification informationoutput unit 311 outputs information indicating a start, a continuation,or an end of the sleep section. In this case, for example, it ispossible to notify friends on social media that the user wakes up, hasslept, or is sleeping. This notification may be a push type notificationor may be a pull type notification. In the case of the pull typenotification, for example, a sleep state can be represented by an iconof a user expressed in a virtual space, and other user can view thevirtual space and recognize that the user is sleeping or awake.

Alternatively, the notification information output unit 311 may outputinformation indicating the length of the sleep section in apredetermined period. In this case, for example, the lack of sleep maybe notified to friends according to whether the use's sleeping time perday is more than or less than an average. As in the above-describedexample, the notification may be output through the virtual space, andrings may be superimposed on the actual user's face by using augmentedreality (AR) technology.

Another example of the processing of the external device control unit309 and the notification information output unit 311 will be describedas an example application of the sleep section detection result.

1-4. Processing Flow of Sleep Section Detection

FIG. 4 is a diagram for describing a processing flow of the sleepsection detection in the first embodiment of the present disclosure. Theprocessing flow shown in FIG. 4 corresponds to the functionalconfiguration of the information processing apparatus 300 describedabove with reference to FIG. 3. That is, a series of processingperformed by a feature amount calculation unit 401 to a matchingadjustment unit 413 may be expressed from a viewpoint different from thefunctions of the respective elements of the information processingapparatus 300. Therefore, the series of processing is performed by theprocessor of the sensor device 100 or the smartphone 200. In thefollowing, the processing of the respective elements of the processingflow will be further described.

The feature amount calculation unit 401 calculates feature amount fromsensor data. Here, the feature amount to be calculated may be one thatcan be restored to raw data or data close to the raw data. For example,in a case where the sensor data is data of the acceleration sensor, thefeature amount calculation unit 401 may calculate an average value or avariance value of acceleration based on a predetermined time (forexample, one minute) as time unit.

The stable section detection unit 403 detects the stable section inwhich the posture of the user is estimated to be in the stable state,based on the feature amount calculated from the sensor data by thefeature amount calculation unit 401. As described above, since thedetected stable section is only the stable section of the posture of thesensor device 100, whether or not the user wears the sensor device 100and is in a stable posture and whether or not the sensor device 100 isdetached and left somewhere are not specified by the stable sectiondetection result alone.

A filter processing unit 405 performs filter processing on the stablesection detected by the stable section detection unit 403. For example,the filter processing unit 405 filters the detected stable section basedon the length of the stable section. More specifically, in a case wherethe length of the section is equal to or less than a predetermined time(for example, five minutes), the filter processing unit 405 excludes thecorresponding section from the stable section. When considering that thestable section is used for detecting the sleep section of the user, asleep section having a short time may also exist. However, in such acase, for the reason that the stable section does not include theabove-described specific action section, it is difficult to distinguishthe stable section from a pseudo-stable section occurring for a reasonother than sleep. Therefore, in the present embodiment, the sectionhaving a short time is excluded from the stable section.

The specific action determination unit 407 detects the specific actionsection in which the specific action of the user occurs, based on thefeature amount calculated from the sensor data by the feature amountcalculation unit 401. Furthermore, the specific action determinationunit 407 determines whether or not the stable section is the sleepsection, based on a relationship between the specific action section andthe stable section detected by the stable section detection unit 403 andfiltered by the filter processing unit 405. More specifically, in a casewhere a specific action section is present subsequently to before or/andafter the stable section, the specific action determination unit 407 mayspecify the corresponding stable section and the specific action sectionsubsequent to the stable section as the sleep section.

So far, a result R1 indicating the sleep section is acquired by theprocessing of the feature amount calculation unit 401, the stablesection detection unit 403, the filter processing unit 405, and thespecific action determination unit 407. In the result R1, it can be saidthat the sleep section is specified based on the relationship betweenthe pure stable section and the specific action section, withoutapplying the filter with respect to the sleep section detection result,except that the excessively short stable section is excluded by thefilter processing unit 405. The result R1 may be used as an input ofprocessing of a section combination unit 409 to be described below ormay be output as it is.

The section combination unit 409 combines sections having a close gap inthe sleep section specified by the result R1. More specifically, forexample, in a case where a gap between the sleep sections is equal to orless than a predetermined time (for example, thirty minutes), thesection combination unit 409 combines these sections. For example, asexemplified in the description of the specific action section detectionunit 305, in a case where the condition of the specific action sectionis that the detection values of the acceleration sensor are stable atdifferent values before and after the corresponding section, the sectionin which the posture returns to the same posture as a result of changingthe posture by the user's turning-over and a movement similar thereto isdetected as the specific action section. However, such a section alsomay be included in the sleep section of the user, for example, in a casewhere the section occurs in a sufficiently short time as compared withthe stable section.

The filter processing unit 411 performs filter processing on the stablesection after combination by the section combination unit 409. Forexample, the filter processing unit 411 filters the combined stablesection based on the length of the stable section. More specifically, ina case where a length of a sleep section candidate is equal to or lessthan a predetermined time (for example, thirty minutes), the filterprocessing unit 411 excludes the corresponding section from the stablesection. It is likely that the sleep section that does not reach asufficient length even when combined will be, for example, a falselydetected stable section occurring for a reason other than sleep. Also,according to the method of using the detection result, there is noproblem even though a short sleep section such as a snooze or a nap isnot detected. Therefore, in the present embodiment, the filterprocessing unit 411 excludes the section that does not reach asufficient length.

In a case where the filtering based on the length of the section isperformed in the filter processing unit 405 and/or the filter processingunit 411, a predetermined time that becomes a threshold value isarbitrarily set and is not limited to the above-described example (fiveminutes and thirty minutes). However, in a case where the filtering isperformed by the filter processing units 405 and 411 as in theabove-described example, the threshold time by the filter processingunit 411 (which is used for excluding the excessively short sleepsection even when combined) is longer than the threshold time by thefilter processing unit 405 (which is used for excluding the excessivelyshort stable section).

So far, a result R2 indicating the sleep section is acquired by theprocessing of the section combination unit 409 and the filter processingunit 411 with respect to the result R1. In the result R2, the sleepsections that are specified by the result R1 and have a close gap arecombined (section combination unit 409), and furthermore, the sleepsections that do not reach a sufficient length even when combined areexcluded (filter processing unit 411). Therefore, in the result R2, itcan be said that a weak filter using the gap or length indicated by thedetection result itself is applied with respect to the sleep sectiondetection result. The result R2 may be used as an input of a matchingadjustment unit 413 to be described below or may be output as it is.

The matching adjustment unit 413 adjusts a matching with a behaviorrecognition result by another method in the sleep section specified bythe result R2. More specifically, for example, the matching adjustmentunit 413 adjusts the matching between the result of the behaviorrecognition performed by the behavior recognition unit 230, based on thedetection result of the position detection unit 210 and the sensor 220of the smartphone 200, and the sleep section specified by the result R2.For example, in the sleep section specified by the result R2, in a casewhere the behavior recognition unit 230 recognizes a behavior of“walking” (longer-distance walking, not walking in the house), either orboth of the sleep section or the behavior recognition result isconsidered as an error.

In such a case, for example, the matching adjustment unit 413 mayfixedly prioritize either the sleep section or the behavior recognitionresult. For example, in a case where the sleep section is preferred, thebehavior such as “walking” recognized in the sleep section is ignored.On the contrary, in a case where the behavior recognition result ispreferred, the sleep section in which the behavior such as “walking” isrecognized is determined as being falsely detected. Alternatively, thematching adjustment unit 413 may select the result employed based on thereliability degree of each of the sleep section and the behaviorrecognition result. Also, in a case where the sleep section detectionresult and the behavior recognition result conflict each other, thematching adjustment unit 413 may set the user's behavior in thecorresponding section as “unknown”.

A result R3 indicating the sleep section is acquired through theprocessing of the matching adjustment unit 413 as described above. Inthe result R3, it can be said that a stronger filter is applied to thesleep section specified by the result R2 in consideration of thematching with the behavior recognition result by another method. Theresult R3 is output for use in the application 270 of the smartphone200. As described above, the result R1 and/or the result R2 also areoutput along with the result R3 or instead of the result R3. Therefore,in the present embodiment, for example, the result R1 may be output andthe processing of the section combination unit 409 to the matchingadjustment unit 413 may not be performed. The result R2 may be outputand the processing of the matching adjustment unit 413 may not beperformed.

2. Second Embodiment

FIG. 5 is a block diagram showing a schematic configuration of a systemaccording to a second embodiment of the present disclosure. Referring toFIG. 5, a system 20 includes a sensor device 500, a smartphone 600, anda server 700. The sensor device 500 includes a sensor 110, apre-processing unit 120, and a memory 130. The smartphone 200 includes aposition detection unit 210, a sensor 220, and an application 270. Theserver 700 includes a behavior recognition unit 230, a processing unit240, an integrated analysis unit 250, and a storage 260.

(Sensor Device)

The sensor device 500 is a wearable device as in the sensor device 100according to the first embodiment. The sensor 110, the processing unit120, and the memory 130, which are included in the sensor device 100,are similar to those of the first embodiment. However, the sensor device500 differs from the sensor device 100 according to the firstembodiment, in that data stored in the memory 130 is transmitted to theserver 700 directly or indirectly through a communication device (notshown). The sensor device 500 may transmit data to the smartphone 600 byusing wireless communication such as radio communication such asBluetooth (registered trademark), and the communication device (notshown) of the smartphone 600 may transmit data to the server 700 througha network. Alternatively, the sensor device 500 can directly communicatewith the server 700 through the network.

(Smartphone)

As in the smartphone 200 according to the first embodiment, thesmartphone 600 is a terminal device that is carried by the userseparately from the sensor device 500. The position detection unit 210,the sensor 220, and the application 270, which are included in thesmartphone 600, are elements similar to those of the first embodiment.On the other hand, in the present embodiment, the smartphone 600 doesnot include processing elements such as the behavior recognition unit230, the processing unit 240, and the integrated analysis unit 250. Thatis, in the present embodiment, the smartphone 600 includes theprocessor, but the above-described elements are not realized by theprocessor. The detection results by the position detection unit 210 andthe sensor 220 are transmitted to the server 700 through the network bythe communication device (not shown). Also, data, which is used by theapplication 270, is transmitted from the server 700 through the networkby the communication device (not shown). Furthermore, as describedabove, the smartphone 600 may stop transmitting data from the sensordevice 500 to the server 700.

(Server)

The server 700 is realized by one information processing apparatus or aplurality of information processing apparatuses on the network. Thebehavior recognition unit 230, the processing unit 240, the integratedanalysis unit 250, and the storage 260, which are included in the server700, are elements similar to those included in the smartphone 200according to the first embodiment. Since the functions of these elementsare substantially the same as those of the first embodiment, a detaileddescription thereof will be omitted.

As described above, in the present embodiment, some functions realizedby the smartphone 200 according to the first embodiment are realized bythe server 700. In the present embodiment, the server 700 is aninformation processing apparatus that performs the sleep sectiondetection. The configuration of the system including the serveraccording to the embodiment of the present disclosure is not limited tothe example shown in FIG. 5. For example, some of the behaviorrecognition unit 230, the processing unit 240, and the integratedanalysis unit 250 may be realized by the sensor device 500 or thesmartphone 600. In this case, for example, the device realized by theprocessing unit 240 is the information processing apparatus according tothe embodiment of the present disclosure.

In the present embodiment, in a case where the detection of the sleepsection of the user based on the sensor data acquired by the sensordevice 500 is performed by the server 700, the smartphone 600 may not benecessarily included in the system. In this case, the behaviorrecognition unit 230 and the integrated analysis unit 250 may not beincluded in the server 700, and the data of the sleep section detectedbased on the sensor data by the processing unit 240 may be stored in thestorage 260 as it is.

3. Third Embodiment

Next, a third embodiment of the present disclosure will be described.The present embodiment is similar to the first or second embodiment interms of the device configuration, but is different in the sleep sectiondetection processing performed by the information processing apparatus300 described above with reference to FIG. 3. Therefore, in thefollowing, the difference will be mainly described and a detaileddescription of the points (device configuration) common to theabove-described embodiments will be omitted. In the followingdescription of the third and fourth embodiments, the reference signs ofthe first embodiment (the sensor device 100 and the smartphone 200) arerecited, but the similar configuration is possible to the secondembodiment (the sensor device 500, the smartphone 600, and the server700).

In the present embodiment, the stable section detection unit 303 detectsa section in which the posture of the sensor device 100 is regularlychanged. For example, such a stable section is detected as a section inwhich the acceleration sensor detection value included in the firstsensor data is regularly changed. In a case where the user is in a sleepstate, some examples may be considered. One example is a case where theuser is lying down on a bed and is substantially stationary and asleep.Another example is a case where the user is asleep while sitting on achair in a house or a vehicle. The latter case is a so-called “nod off”state. For example, in the latter case, a regular body movement such asup-and-down movement of a head occurs. In the present embodiment, such astate is detected as a sleep state.

More specifically, for example, in a case where the stable sectiondetection unit 303 detects a stable section, the specific action sectiondetection unit 305 detects a section in which an image or a voice of auser shows a characteristic associated with a sleep. In this case, thesecond sensor data acquired by the sensor data acquisition unit 301includes the image or the voice of the user that is acquired by thecamera or the microphone. For example, the specific action sectiondetection unit 305 may detect, as a specific action section, a sectionin which it is recognized that the user closes his or her eyes by imagedata contained in the second sensor data. That the user has closed hisor her eyes may be detected by, for example, another sensor detecting amovement of eyes or an electro-oculogram. Also, the specific actionsection detection unit 305 may detect, as a specific action section, asection in which it is recognized that the user emits a specific sound,based on audio data contained in the second sensor data. Here, such aspecific sound is, for example, a sound corresponding to a sleep breathor a snoring.

In the present embodiment, in a case where the stable section detectedby the stable section detection unit 303 and the specific action sectiondetected by the specific action section detection unit 305 areconcurrent, the sleep section detection unit 307 detects the sleepsection including the stable section. That is, in the presentembodiment, a section in which the posture of the sensor device 100 isregularly changed in the stable section and the image or the voice ofthe user shows a characteristic associated with a sleep (closing eyes,making a sleep breath, snoring, or the like)

4. Fourth Embodiment

Next, a fourth embodiment of the present disclosure will be described.The present embodiment is configured by, for example, a combination ofthe first to third embodiments. In the present embodiment, a pluralityof detectors is selectively used for detecting a sleep section of auser.

FIG. 6 is a diagram for describing a selective use of detectors in afourth embodiment of the present disclosure. Referring to FIG. 6, in thepresent embodiment, when sensor data is input and the sleep sectiondetection processing is started, a detector selection unit 801 selectsone or more detectors to be used. In the detectors, for example, thereare a body motion detector 703, a neck motion detector 805, and aclosed-eye detector 807. The detection results by one or more detectorselected among these detectors by the detector selection unit 801 arecombined by a determination result combination unit 809 and are outputas a sleep section detection result.

The detector selection unit 801 is realized by, for example, theprocessor of the sensor device 100 or the smartphone 200. The detectorselection unit 801 selects one or more detectors to be used, forexample, according to whether or not the sensor device 100 is attachedto the user, how much a battery residual quantity of the sensor device100 remains, or what action of the user (including simple positioninformation) is recognized by the behavior recognition unit 230 of thesmartphone 200 side. All selectable detectors may be selected.

The body motion detector 803 includes, for example, sensing by theacceleration sensor included in the sensor 110, pre-processing of thedetection value in the pre-processing unit 120, and detection of theuser's body motion based on the detection value and detection of thesleep section based on that in the processing unit 240 (for example,detection of the sleep section using the detection of the section inwhich the posture of the user is unchanged). Therefore, in a case wherethe detector selection unit 801 selects the body motion detector 803, aseries of processing is performed for detecting a sleep section based onthe detection of the user's body motion as described above.

The neck motion detector 805 includes, for example, sensing by theacceleration sensor included in the sensor 110, pre-processing of thedetection value in the pre-processing unit 120, and detection of theuser's neck motion based on the detection value and detection of thesleep section based on that in the processing unit 240 (for example,detection of the sleep section using the detection of the section inwhich the user's neck (head) motion is regular (nod-off section)).Therefore, in a case where the detector selection unit 801 selects theneck motion detector 805, a series of processing is performed fordetecting a sleep section based on the detection of the user's neck(head) motion as described above.

The closed-eye detector 807 includes, for example, capturing of an imageby the camera included in the sensor 110, pre-processing of image datain the pre-processing unit 120, and detection of whether or not the usercloses his or her eyes based on the image data and detection of thesleep section based on that in the processing unit 240 (for example,detection of the sleep section on the condition that the body motion ofthe user is regular and the user closes his or her eyes). Therefore, ina case where the detector selection unit 801 selects the closed-eyedetector 807, a series of processing is performed for detecting a sleepsection based on the detection of whether or not the user closes his orher eyes as described above.

As described above, the determination result combination unit 809combines the detection results by the selected one or more detectors anddetermines the sleep section. The determination result combination unit809 is realized as, for example, the processing unit 240 of thesmartphone 200. In a case where the selected detector is single, thedetermination result combination unit 809 may output the detectionresult of the selected detector as it is. Also, in a case where theselected detector is plural, the determination result combination unit809 may perform, for example, a logical OR operation on the sleepsection detection results by the plurality of selected detectors. Inthis case, the section detected as the sleep section in any one of thedetectors is output as the sleep section. Alternatively, thedetermination result combination unit 809 may perform a logical ANDoperation on the sleep section detection results by the plurality ofselected detectors. In this case, the sections detected as the sleepsection in all the selected detectors are output as the sleep sections.

Alternatively, the determination result combination unit 809 may acquirescores indicating probability of the detection result in the respectiveselected detectors, weight the detection results, and determine thesleep section based on the sum of the scores. In this case, therespective detectors, for example, the body motion detector 803, theneck motion detector 805, and the closed-eye detector 807, output thescores indicating the probability of the detection result to thedetermination result combination unit 809.

In the present embodiment, by selectively using the plurality ofdetectors for detecting the sleep section of the user, for example, thedetection using the smartphone 200 may be continued, the sensor to beused may be switched according to the battery residual quantity of thesensor device 100, or the method of detecting an optimal sleep sectionaccording to situations may be used, even while the sensor device 100 isdetached.

5. Example Application of Detection Result

Next, example application of the sleep section detection resultaccording to the embodiment of the present disclosure will be described.As described above, in the embodiment of the present disclosure, forexample, in a case where the start of the sleep section is detected, thesleep section detection result is applied by outputting the controlsignal of the external device and outputting information for notifyingother user of the sleep section detection result. In the following,example application of these sleep section detection result will bedescribed with reference to a more specific example.

(Control of External Device)

As an example in which the external device control unit 309 of theinformation processing apparatus 300 output the control signal in a casewhere the start of the sleep section is detected, there are an examplein which a control signal for stopping or pausing the external device asdescribed above is output and an example in which a control signal forcausing the external device to set an alarm based on the start time ofthe sleep section is output.

In addition, for example, in a case where the start of the sleep sectionis detected, the external device control unit 309 may output a controlsignal for performing a predetermined operation to the external device.As an example, the external device control unit 309 may output a controlsignal for performing backup or upload, analysis, or the like withrespect to an information processing terminal such as a personalcomputer. When such processing is performed while the user uses theinformation processing terminal, there is a probability that hinders theoperation of the information processing terminal desired by the user inorder for consumption of device resources. Therefore, when assuming thatsuch processing can be performed in a case where the start of the sleepsection of the user is detected, the processing can be completed withouthindering the operation of the user.

(Notification of Other User)

As an example in which the notification information output unit 311 ofthe information processing apparatus 300 output information fornotifying other user of the sleep section detection result, there are anexample in which information indicating a start, a continuation, or anend of the sleep section is output as described above and an example inwhich information indicating the length of the sleep section in apredetermined period is output.

In addition, for example, in a case where schedule information of theuser is acquired and it is determined that the sleep state of the userhinders the execution of the schedule, the notification informationoutput unit 311 may output notification to request a friend to take abehavior that wakes the user (for example, making a phone call). In thiscase, the external device control unit 309 may output a control signalto the external device (as described above, including other functionsrealized by the same processor) so as to sound an alarm at the time whenthe user must wake for the execution of the schedule, and in a casewhere the user does not wake in spite of the alarm (in a case where theend of the sleep section is not detected), the notification informationoutput unit 311 may output the notification to other user.

Also, for example, the notification information output unit 311 mayinterwork with other information processing terminal, adjust theschedule according to the wake-up time of the user belonging to apredetermined group such as friends, notify the adjusted schedule toeach user, and transmit the notification to request sounding of alarmwith respect to an information processing terminal of a user who seemsto be late for the adjusted schedule. At this time, a distance from acurrent position of each user to a place (destination) where a scheduledevent is executed may be considered. That is, the output of thenotification may be adjusted such that a user near the destination wakesimmediately before the start time of the event and a user far from thedestination wakes long before the start time.

Also, for example, the notification information output unit 311 mayoutput information to other user on the condition that a certain userhas woken (the sleep section has been finished). For example, in a casewhere teleconference intends to be performed in a certain environmentwith time difference, when a user participating in the early morningwoken, the start of the conference may be notified to other userparticipating in the day. In this way, the contact or notification issmoothly performed in a case where the user want to do something if theuser wakes but does not wake.

As another example application of the sleep section detection resultaccording to the embodiment of the present disclosure, not limited tothe external device control unit 309 or the notification informationoutput unit 311, the percentage of users who have woken at the sleepingtime in countries or regions may be statistically grasped based on thedetection results of the sleep sections of users in the correspondingcountries and regions and may be used as indexes of how much the eventsoccurring at that time (for example, midnight sports broadcasting) areattracted. Also, for example, the percentage of sleeping users in acertain region may be statistically grasped based on the detectionresults of the sleep sections of the users in the corresponding regionand be used as the criteria of whether or not infrastructure such as aradio-communication base station is operated in a low power consumptionmode.

6. Hardware Configuration

Next, with reference to FIG. 7, a hardware configuration of aninformation processing apparatus according to an embodiment of thepresent disclosure will be described. FIG. 7 is a block diagram showinga hardware configuration of the information processing apparatusaccording to an embodiment of the present disclosure. An informationprocessing apparatus 900 which is shown may achieve the sensor device,the smartphone, and the server in the above described embodiments, forexample.

The information processing apparatus 900 includes a central processingunit (CPU) 901, read only memory (ROM) 903, and random access memory(RAM) 905. Further, the information processing apparatus 900 may alsoinclude a host bus 907, a bridge 909, an external bus 911, an interface913, an input device 915, an output device 917, a storage device 919, adrive 921, a connection port 923, and a communication device 925.Furthermore, the information processing apparatus 900 may include animaging device 933 and a sensor 935 as necessary. The informationprocessing apparatus 900 may also include, instead of or along with theCPU 901, a processing circuit such as a digital signal processor (DSP)or an application specific integrated circuit (ASIC).

The CPU 901 functions as an arithmetic processing unit and a controlunit and controls an entire operation or a part of the operation of theinformation processing apparatus 900 according to various programsrecorded in the ROM 903, the RAM 905, the storage device 919, or aremovable recording medium 927. The ROM 903 stores programs andarithmetic parameters used by the CPU 901. The RAM 905 primarily storesprograms used in execution of the CPU 901 and parameters and the likevarying as appropriate during the execution. The CPU 901, the ROM 903,and the RAM 905 are connected to each other via the host bus 907configured from an internal bus such as a CPU bus or the like. Inaddition, the host bus 907 is connected to the external bus 911 such asa peripheral component interconnect/interface (PCI) bus via the bridge909.

The input device 915 is a device operated by a user, such as a mouse, akeyboard, a touch panel, buttons, a switch, and a lever. Also, the inputdevice 915 may be a remote control device using, for example, infraredlight or other radio waves, or may be an external connection device 929such as a cell phone compatible with the operation of the informationprocessing apparatus 900. The input device 915 includes an input controlcircuit that generates an input signal on the basis of information inputby the user and outputs the input signal to the CPU 901. The user inputsvarious kinds of data to the information processing apparatus 900 andinstructs the information processing apparatus 900 to perform aprocessing operation by operating the input device 915.

The output device 917 is configured from a device capable of visually oraurally notifying the user of acquired information. For example, theoutput device 917 may be: a display device such as a liquid crystaldisplay (LCD), a plasma display panel (PDP), or an organicelectro-luminescence (EL) display; an audio output device such as aspeaker or headphones; or a printer. The output device 917 outputsresults obtained by the processing performed by the informationprocessing apparatus 900 as video in the form of text or an image or asaudio in the form of audio or sound.

The storage device 919 is a device for storing data configured as anexample of a storage unit of the information processing apparatus 900.The storage device 919 is configured from, for example, a magneticstorage device such as a hard disk drive (HDD), a semiconductor storagedevice, an optical storage device, or a magneto-optical storage device.This storage device 919 stores programs to be executed by the CPU 901,various data, and various data obtained from the outside.

The drive 921 is a reader/writer for the removable recording medium 927such as a magnetic disk, an optical disc, a magneto-optical disk, or asemiconductor memory, and is built in or externally attached to theinformation processing apparatus 900. The drive 921 reads outinformation recorded on the attached removable recording medium 927, andoutputs the information to the RAM 905. Further, the drive 921 writesthe record on the attached removable recording medium 927.

The connection port 923 is a port for allowing devices to directlyconnect to the information processing apparatus 900. Examples of theconnection port 923 include a universal serial bus (USB) port, anIEE1394 port, and a small computer system interface (SCSI) port. Otherexamples of the connection port 923 may include an RS-232C port, anoptical audio terminal, and a high-definition multimedia interface(HDMI) (registered trademark) port. The connection of the externalconnection device 929 to the connection port 923 may enable the variousdata exchange between the information processing apparatus 900 and theexternal connection device 929.

The communication device 925 is a communication interface configuredfrom, for example, a communication device for establishing a connectionto a communication network 931. The communication device 925 is, forexample, a wired or wireless local area network (LAN), Bluetooth(registered trademark), a communication card for wireless USB (WUSB), orthe like. Alternatively, the communication device 925 may be a routerfor optical communication, a router for asymmetric digital subscriberline (ADSL), a modem for various communications, or the like. Thecommunication device 925 can transmit and receive signals and the likeusing a certain protocol such as TCP/IP on the Internet and with othercommunication devices, for example. The communication network 931connected to the communication device 925 is configured from a networkwhich is connected via wire or wirelessly and is, for example, theInternet, a home-use LAN, infrared communication, radio wavecommunication, and satellite communication.

The imaging device 933 is a device which images a real space by use ofvarious members including an image sensor such as a charge coupleddevice (CCD) or a complementary metal oxide semiconductor (CMOS) and alens for controlling image formation of a subject on the image sensor,and generates a pickup image. The imaging device 933 may image a stillimage or a moving image.

The sensor 935 is any of various sensors such as an acceleration sensor,a gyro sensor, a magnetic field sensor, an optical sensor, and a soundsensor. For example, the sensor 935 acquires information related to thestate of the information processing apparatus 900 itself, such as theposture of the housing of the information processing apparatus 900, orinformation related to the peripheral environment of the informationprocessing apparatus 900, such as the brightness or noise around theinformation processing apparatus 900. Further, the sensor 935 mayinclude a global positioning system (GPS) sensor which measures thelatitude, the longitude, and the altitude of the apparatus by receivinga GPS signal.

Heretofore, an example of the hardware configuration of the informationprocessing apparatus 900 has been shown. Each of the structural elementsdescribed above may be configured using a general-purpose material, ormay be configured from hardware dedicated to the function of eachstructural element. The configuration may be changed as appropriateaccording to the technical level at the time of carrying outembodiments.

7. Supplemental Remarks

Embodiments of the present disclosure encompass an informationprocessing apparatus (client apparatus or server apparatus) and systemas described in the foregoing, an information processing method executedby an information processing apparatus or system, a program for causingan information processing apparatus to function, and a non-transitorycomputer readable medium storing such a program, for example.

The preferred embodiments of the present disclosure have been describedabove with reference to the accompanying drawings, whilst the presentdisclosure is not limited to the above examples, of course. A personskilled in the art may find various alterations and modifications withinthe scope of the appended claims, and it should be understood that theywill naturally come under the technical scope of the present disclosure.

In addition, the effects described in the present specification aremerely illustrative and demonstrative, and not limitative. In otherwords, the technology according to the present disclosure can exhibitother effects that are evident to those skilled in the art along with orinstead of the effects based on the present specification.

Additionally, the present technology may also be configured as below.

(1)

An information processing apparatus including:

a stable section detection unit configured to detect a stable section ofa posture of a sensor device that a user wears, based on first sensordata provided from the sensor device;

a specific action section detection unit configured to detect a specificaction section in which a specific action of the user occurs, based onsecond sensor data; and

a sleep section detection unit configured to detect a sleep section inwhich the user is in a sleep state, based on a relationship between thestable section and the specific action section.

(2)

The information processing apparatus according to (1),

wherein the stable section is a section in which the posture of thesensor device is unchanged.

(3)

The information processing apparatus according to (2),

wherein the specific action section is a section in which a posture ofthe user is changed, and

wherein in a case where the stable section and the specific actionsection are repeated, the sleep section detection unit detects a sleepsection that includes the stable section and the specific actionsection.

(4)

The information processing apparatus according to (3),

wherein both the first sensor data and the second sensor data includeacceleration sensor data.

(5)

The information processing apparatus according to (1),

wherein the stable section is a section in which the posture of thesensor device is regularly changed.

(6)

The information processing apparatus according to (5),

wherein the specific action section is a section in which an image or avoice of the user shows a characteristic associated with a sleep, and

wherein in a case where the stable section and the specific actionsection are concurrent, the sleep section detection unit detects a sleepsection that includes the stable section.

(7)

The information processing apparatus according to (6),

wherein the first sensor data includes acceleration sensor data,

wherein the second sensor data includes image data, and

wherein the specific action section is a section in which it isrecognized that the user closes eyes based on the image data.

(8)

The information processing apparatus according to (6),

wherein the first sensor data includes acceleration sensor data,

wherein the second sensor data includes audio data, and

wherein the specific action section is a section in which it isrecognized that the user emits a specific sound based on the audio data.

(9)

The information processing apparatus according to any one of (1) to (8),

wherein the sleep section detection unit detects the sleep sectionfurther based on user behavior that is recognized based on sensor datadifferent from the first and second sensor data.

(10)

The information processing apparatus according to any one of (1) to (9),further including:

an external device control unit configured to output a control signal ofan external device in a case where a start of the sleep section isdetected.

(11)

The information processing apparatus according to (10),

wherein the external device control unit outputs a control signal forstopping or pausing the external device.

(12)

The information processing apparatus according to (10),

wherein the external device control unit outputs the control signal forcausing the external device to set an alarm based on a start time of thesleep section.

(13)

The information processing apparatus according to any one of (1) to(12), further including:

a notification information output unit configured to output informationfor notifying another user of a detection result of the sleep section.

(14)

The information processing apparatus according to (13),

wherein the notification information output unit outputs informationindicating a start, a continuation, or an end of the sleep section.

(15)

The information processing apparatus according to (13),

wherein the notification information output unit outputs informationindicating a length of the sleep section in a predetermined period.

(16)

An information processing method including:

detecting a stable section of a posture of a sensor device that a userwears, based on first sensor data provided from the sensor device;

detecting a specific action section in which a specific action of theuser occurs, based on second sensor data; and

detecting, by a processor, a sleep section in which the user is in asleep state, based on a relationship between the stable section and thespecific action section.

(17)

A program for causing a computer to execute:

a function of detecting a stable section of a posture of a sensor devicethat a user wears, based on first sensor data provided from the sensordevice;

a function of detecting a specific action section in which a specificaction of the user occurs, based on second sensor data; and

a function of detecting a sleep section in which the user is in a sleepstate, based on a relationship between the stable section and thespecific action section.

REFERENCE SIGNS LIST

-   10, 20 system-   100 sensor device-   110 sensor-   120 pre-processing unit-   130 memory-   200 smartphone-   210 position detection unit-   220 sensor-   230 behavior recognition unit-   240 processing unit-   250 integrated analysis unit-   260 storage-   270 application-   300 information processing apparatus-   301 acquisition unit-   303 stable section detection unit-   305 specific action section detection unit-   307 sleep section detection unit-   309 external device control unit-   311 notification information output unit

1. An information processing apparatus comprising: a stable sectiondetection unit configured to detect a stable section of a posture of asensor device that a user wears, based on first sensor data providedfrom the sensor device; a specific action section detection unitconfigured to detect a specific action section in which a specificaction of the user occurs, based on second sensor data; and a sleepsection detection unit configured to detect a sleep section in which theuser is in a sleep state, based on a relationship between the stablesection and the specific action section.
 2. The information processingapparatus according to claim 1, wherein the stable section is a sectionin which the posture of the sensor device is unchanged.
 3. Theinformation processing apparatus according to claim 2, wherein thespecific action section is a section in which a posture of the user ischanged, and wherein in a case where the stable section and the specificaction section are repeated, the sleep section detection unit detects asleep section that includes the stable section and the specific actionsection.
 4. The information processing apparatus according to claim 3,wherein both the first sensor data and the second sensor data includeacceleration sensor data.
 5. The information processing apparatusaccording to claim 1, wherein the stable section is a section in whichthe posture of the sensor device is regularly changed.
 6. Theinformation processing apparatus according to claim 5, wherein thespecific action section is a section in which an image or a voice of theuser shows a characteristic associated with a sleep, and wherein in acase where the stable section and the specific action section areconcurrent, the sleep section detection unit detects a sleep sectionthat includes the stable section.
 7. The information processingapparatus according to claim 6, wherein the first sensor data includesacceleration sensor data, wherein the second sensor data includes imagedata, and wherein the specific action section is a section in which itis recognized that the user closes eyes based on the image data.
 8. Theinformation processing apparatus according to claim 6, wherein the firstsensor data includes acceleration sensor data, wherein the second sensordata includes audio data, and wherein the specific action section is asection in which it is recognized that the user emits a specific soundbased on the audio data.
 9. The information processing apparatusaccording to claim 1, wherein the sleep section detection unit detectsthe sleep section further based on user behavior that is recognizedbased on sensor data different from the first and second sensor data.10. The information processing apparatus according to claim 1, furthercomprising: an external device control unit configured to output acontrol signal of an external device in a case where a start of thesleep section is detected.
 11. The information processing apparatusaccording to claim 10, wherein the external device control unit outputsa control signal for stopping or pausing the external device.
 12. Theinformation processing apparatus according to claim 10, wherein theexternal device control unit outputs the control signal for causing theexternal device to set an alarm based on a start time of the sleepsection.
 13. The information processing apparatus according to claim 1,further comprising: a notification information output unit configured tooutput information for notifying another user of a detection result ofthe sleep section.
 14. The information processing apparatus according toclaim 13, wherein the notification information output unit outputsinformation indicating a start, a continuation, or an end of the sleepsection.
 15. The information processing apparatus according to claim 13,wherein the notification information output unit outputs informationindicating a length of the sleep section in a predetermined period. 16.An information processing method comprising: detecting a stable sectionof a posture of a sensor device that a user wears, based on first sensordata provided from the sensor device; detecting a specific actionsection in which a specific action of the user occurs, based on secondsensor data; and detecting, by a processor, a sleep section in which theuser is in a sleep state, based on a relationship between the stablesection and the specific action section.
 17. A program for causing acomputer to execute: a function of detecting a stable section of aposture of a sensor device that a user wears, based on first sensor dataprovided from the sensor device; a function of detecting a specificaction section in which a specific action of the user occurs, based onsecond sensor data; and a function of detecting a sleep section in whichthe user is in a sleep state, based on a relationship between the stablesection and the specific action section.